---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert-base-uncased-finetuned-emotion

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1537
- Accuracy: 0.935
- F1: 0.9349

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8025        | 1.0   | 250  | 0.2643          | 0.917    | 0.9171 |
| 0.2032        | 2.0   | 500  | 0.1698          | 0.9325   | 0.9324 |
| 0.133         | 3.0   | 750  | 0.1510          | 0.9405   | 0.9412 |
| 0.1035        | 4.0   | 1000 | 0.1463          | 0.938    | 0.9378 |
| 0.0867        | 5.0   | 1250 | 0.1395          | 0.941    | 0.9409 |
| 0.0726        | 6.0   | 1500 | 0.1482          | 0.9405   | 0.9407 |
| 0.0624        | 7.0   | 1750 | 0.1550          | 0.934    | 0.9339 |
| 0.0539        | 8.0   | 2000 | 0.1537          | 0.935    | 0.9349 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1